Method and system for identifying and anticipating adverse drug events

ABSTRACT

The present invention is a system and method for anticipating potential Adverse Drug Events (ADE) in a patient&#39;s medication regimen by integrating data typically located in laboratory and pharmacy information systems and filtering the data using predefined criteria. The present invention includes a system for anticipating a possible ADE through the use of a search engine that compares integrated data from laboratory and pharmacy information systems and compares it to predefined ADE rules defining normal ranges for a particular laboratory test. If an abnormal test value is received and a drug in the patient&#39;s medication regimen satisfies a drug included in an ADE rule then an alert procedure is triggered which allows for a period of time wherein the patient&#39;s lab and pharmacy data is monitored in order to determine if a proper corrective action is undertaken, and if no corrective action or an improper corrective action is taken within that period of time, the healthcare provider is warned of a potential ADE.

CROSS-REFERENCE TO RELATED APPLICATION(S)

This application claims priority from U.S. provisional application No.60/272,019, filed Feb. 28, 2001 the contents of which are incorporatedherein in its entirety.

TECHNICAL FIELD

This invention relates to a method and system for managing andanticipating adverse drug events (“ADE”). More particularly, theinvention relates to a method and system for integrating and using datafrom a medical facility's pharmacy and laboratory information systems toanticipate potential ADEs in a patient's medication regiment.

BACKGROUND OF THE INVENTION

A number of preventable patient care errors occur because theprescription of medication to a patient is done without first consultinga patient's laboratory results. Some patients have had drugscontinuously administered to them for hours or days after toxic levelsfor that drug are recorded by the lab. Some patients have receivedparticular medication long after the laboratory has documented signs ofdrug-related side effects. Others have received erroneous laboratorytest results because their medication interferes with the laboratorytests they are undergoing. Still others have received medications evenafter the patient's lab result indicates that it is dangerous to do so.All these errors, and many more not mentioned, could have all beenprevented if a patients laboratory results were consulted prior toprescribing or administrating a medication.

These errors occur for many reasons. At times, a physician is orderingcertain medications at a site remote from a medical facility and so isnot able to review a patient's chart. At times, the physician isn't evenaware of contraindications for certain medication because testsrevealing those contraindications have not been performed or had notbeen recorded in a patient's chart. In some instances, even thoughcontraindications for certain medications are documented, the physiciansimply fails to detect the contraindications from the patient's chart.Consequently, some oversight is needed in order to determine if mistakesare made or if an ADE might occur in a patient's medication regimen.

Since a pharmacy department of a medical facility is typicallyresponsible for filling all prescriptions and dispensing all medicationsto patients, it is often the only means for catching some of theseerrors. To that extent, some pharmacies have information systems inplace that can alert the pharmacist that an ADE would occur betweendrugs administered to a patient. However, these information systems aretypically limited to detecting a potential ADE between drugsadministered to a patient These pharmacy information systems are notcapable of predicting an ADE based on a patient's physiologicalcondition, because these systems typically do not monitor or have accessor have the capability to process a patient's laboratory results.

A laboratory department of a medical facility typically performs testsand analyzes specimens (such as blood, urine, cell cultures, etc.)received from a patient and stores these results on a laboratoryinformation system. In many instances, the test results and analysis onpatient specimens are germane to the administration of medication.However, despite this symbiotic relationship between the laboratory andthe pharmacy, these two departments and their work processes, personnel,and particularly their information systems, rarely effectivelycommunicate with each other.

In many clinical settings, there are a number of factors which preventthe integration of data from the laboratory and the pharmacy.Compatibility issues between the separate information systems is often amajor roadblock to integration. The desire of each department to haveinformation systems particularly adapted for their respective needs maybe another. The cost of integrating data from both information system iscertainly another prohibiting factor. As a result, there is a need for acommercial system that integrates and uses laboratory and pharmacy datato anticipate potential ADEs in a patient's medication regimen.

Thus, significant improvements in patient care can be achieved bydeveloping a cost effective, commercial, turnkey system that integratesdata collected and stored in pharmacy and laboratory information systemsand utilizes this data to anticipate potential ADEs in a patient'smedication regimen.

BRIEF SUMMARY OF THE INVENTION

The present invention is a system and method for anticipating potentialADEs in a patient's medication regimen by integrating data typicallylocated in laboratory and pharmacy information systems and filtering thedata using predefined criteria. The present invention includes a systemfor anticipating a possible ADE through the use of a search engine thatcompares integrated data from laboratory and pharmacy informationsystems and compares it to predefined ADE rules defining normal rangesfor a particular laboratory test. If an abnormal test value is receivedand a drug in the patient's medication regimen satisfies a drug includedin an ADE rule then an alert procedure is triggered which allows for aperiod of time wherein the patient's lab and pharmacy data is monitoredin order to determine if a proper corrective action is undertaken, andif no corrective action or an improper corrective action is taken withinthat period of time, the healthcare provider is warned of a potentialADE.

In one embodiment, the ADE monitoring system is utilized in anapplication service provider environment (ASP) wherein the ADEmonitoring system is comprised of at least one server having acommunication link to a computer network. In this embodiment, a secureintranet provides the conduit through which data is downloaded from themedical facility, and users access the ADE monitoring system.

In another embodiment, a method for detecting an ADE is disclosed whichincludes extracting information within pharmacy and lab data andrespectively placing it into a normalized drug table or a normalized labtable. The data within these tables are then filtered by an ADE searchengine which searches an ADE rule database to see if it matches anypredefined ADE rule. If a match is made an alert procedure is activated.

While several embodiments are disclosed, still other embodiments of thepresent invention will become apparent to those skilled in the art fromthe following detailed description. As will be realized, the inventionis capable of modifications in various obvious aspects, all withoutdeparting from the spirit and scope of the present invention.Accordingly, the drawings and detailed description are to be regarded asillustrative in nature and not restrictive.

BRIEF DESCRIPTION OF THE ATTACHMENTS

FIG. 1 is a block diagram representing an embodiment of an ADEmonitoring system in an application service provider environment.

FIG. 2 is a diagram representing the hardware components of the ADEmonitoring system of FIG. 1.

FIG. 3 is a block diagram representing an alternative embodiment of anADE monitoring system in a stand-alone environment.

FIG. 4 is a diagram representing an embodiment of the ADE monitoringsystem.

FIG. 5 is a block diagram representing an embodiment of a data importprocedure.

FIG. 6 is a block diagram representing an embodiment of an ADEmonitoring procedure.

FIG. 7 is an embodiment of an ADE rule.

FIG. 8 a is flow chart representing the ADE monitoring process.

FIG. 8 b is a continuation of FIG. 8 a.

FIG. 9 is a diagram depicting detection of an abnormal lab result.

FIG. 10 is a diagram depicting concurrent lab and drug features.

FIG. 11 is a diagram depicting filtering for specific details.

FIG. 12 a is a timeline depicting a corrective action comprising of anormal lab result.

FIG. 12 b is a timeline depicting a corrective action comprising of adiscontinuation of a drug.

FIG. 12 c is a timeline depicting a corrective action comprising of achange in dosage.

FIG. 13 is a timeline depicting an adjustment to an action date by adanger multiplier and a formula to calculate the adjustment.

FIG. 14 is a timeline depicting an adjustment to an action date by amomentum multiplier and a formula to calculate the momentum multiplierand the adjustment to the action date.

FIG. 15 a is an embodiment of a patient graph.

FIG. 15 a is an embodiment of a patient table.

FIG. 16 is an embodiment of a patient alert.

FIG. 17 is an embodiment of a main summary screen.

FIG. 18 is an embodiment of a main screen.

FIG. 19 a is an embodiment of a rule maintenance screen.

FIG. 19 b is a continuation of the screen of FIG. 19 a.

FIG. 20 is an embodiment of a search screen.

DETAILED DESCRIPTION OF THE INVENTION

The subject invention is a system and method for monitoring patientdrug/lab interactions by integrating data typically located inlaboratory and pharmacy information systems and comparing it topredefined ADE rules. It is also contemplated that physiological data(such as blood pressure or heart rate) or patient information,obtainable from computer systems within a health care facility, can alsobe integrated into the disclosed invention in a manner similar to thatdescribed for the pharmacy and laboratory systems.

As will be explained in greater detail below, the subject inventionincludes a system configuration which facilitates data transfer, a dataimport procedure which integrates laboratory and pharmacy data, an ADEmonitoring procedure which performs an extensive search for potentialADE, an alert generation procedure for notifying medical facilities ofpotential ADE, report generating functions for arranging the display ofdata, and a user interface which allows for simple operation of the ADEmonitoring system.

A. System Configuration

As shown in FIGS. 1 and 2, an embodiment of an ADE monitoring system 10in accordance with the subject invention is shown. This embodiment iscomprised of a central processor 11 having included therein a number oftask oriented applications. The central processor 11 can be any computerknown to those skilled in the art, including standard attachments andcomponents thereof (e.g., a disk drive, hard drive, CD/DVD player ornetwork server that communicates with a CPU and main memory, a soundboard, a keyboard and mouse, and a monitor). The processor of the CPU inthe computer may be any conventional general-purpose single- ormulti-chip microprocessor. In addition, the processor may be anyconventional special purpose processor such as a digital signalprocessor or a graphics processor. The microprocessor can includeconventional address lines, conventional data lines, and one or moreconventional control lines.

As shown in FIG. 2, in one embodiment, the ADE monitoring system 20 isutilized in an application service provider environment (“ASP”)accessible to a plurality of users and medical facilities through asecure intranet. In this embodiment, the central processor 11 includes aweb site hosted by at least one web server 21 in communication with theintranet. The central processor 11 may also include a plurality of webservers 21, database servers 22, application servers 23, or directoryservers 24, and may run on a variety of platforms known in the art,including but not limited to, SQL Server 2000, Windows 2000, ActiveDirectory and IIS.

As shown in FIG. 3, in another embodiment, the ADE monitoring system 30is configured to operate in a stand-alone environment, located within amedical facility. Data from laboratory 41 and pharmacy 42 informationsystems may be compiled and transmitted by a FTP server 43 through aLocal Area Network (LAN).

As shown in FIGS. 1 and 3, data from laboratory 31 and pharmacy 32information systems may be compiled and transmitted to the ADEmonitoring system 10 by a File Transfer Protocol (“FTP”) server 33through a router 34 in communication with the ADE monitoring system 30via a computer network such as a secure intranet or a LAN. In otherembodiments, telephonic means or even direct hard wire connections canbe utilized for transmitting data to the ADE monitoring system 10. Thedata transfers are typically initiated by a medical facility, and can betransmitted periodically or may be transferred dynamically as the datais created. In one embodiment, the data is encrypted prior totransmission to secure the privacy of the information.

As shown in FIGS. 1, 2, and 4, in one embodiment, the central processor11 includes software applications or computer instructions located onapplication servers 23. As will be explained further below, and morespecifically in the sections pertaining to their function, theapplications coordinate the functional components of the ADE monitoringsystem 10. These applications may include common software componentsthat are commercially sold, as well as proprietary applicationsspecifically developed to perform specific functions in the ADEmonitoring system.

A Patient Data Import Application 42 is included to receive, validate,and format pharmacy and lab data received from a medical facility. AnAdverse Drug Event Application 43 is included to correlate and examinepharmacy and lab data for each patient, and to generate an alert whenthese criteria do not comply with predefined criteria. A User AccessApplication 46 may also be included for limiting access to the ADEmonitoring system 10 to authorized individuals and for limiting accessto information. The User Access Application typically works inconjunction with a User Directory 45 located on a directory server 24.The User Directory 45 is comprised of a database of authorized users anda level of accessibility allowed for each. An Administration Applicationmay also be included for organizing and maintaining databases pertainingto particular medical facilities and users. A report generationapplication such as Crystal Reports may also be included.

B. Importing Data

As shown in FIGS. 5 and 6, in one embodiment, data records from ahealthcare facility is transmitted to the ADE monitoring system througha secure intranet. The ADE monitoring system 10 first subjects the datarecord to a validation process (block 54) to verify that the data recordis in a known format and to verify that it is complete. Once the datarecord is verified, it is then reformatted by a reformatting process(block 55) to be compatible with data structure employed by a databasewherein the data is stored.

If an error occurred in the transmission of the data record or if thedata record is improperly formatted, an exception handling procedure(block 58) is triggered. The exception handling procedure (block 58)includes the steps of creating an error message and posting it on anerror log which notes the time and date of the error. Also, anelectronic message, preferably an E-mail, is sent to the healthcareprovider sending the data record to notify it of the error.

A pharmacy information system 51 will typically provide the ADEmonitoring system 10 with pharmacy data for each patient and alaboratory information system 52 typically provides informationpertaining to lab tests. A data record imported from a pharmacyinformation system Will typically include information pertaining to amedication prescribed to a patient and the logistics as to how themedication is to be administered. A data record from a lab informationsystem typically provides data pertaining to lab tests for each patient.Lab or pharmacy data is extracted from their respective data records andthis data is then correlated with records pertaining to the same patientID, and stored within a database. In this embodiment, a pharmacydatabase 56 stores pharmacy data and a laboratory database 57 storeslaboratory data.

The data record can be an ASCII file or it can be formatted in any knownmanner. A pharmacy data record will typically include data fieldscontaining a patient ID, a doctor ID, the drug administered, a dosage, atime of dosage, a begin date, and a discontinuance date. A lab datarecord will typically include data fields for a patient ID, a doctor ID,a lab test performed, the test result, the date and time of the test.

In one embodiment, a normalized table called a daily record is createdfrom data extracted from a pharmacy data record and stored within thepharmacy database 56. The table is comprised of a chronological sequenceof records, with each record having data fields identifying a drug, adrug dosage given or to be given, and a time and date when the drugdosage is administered or will be administered. Each record alsoincludes a data field which represents the total dosage for a particulardrug within a 24 hour period from the time the drug is or will be given.A new record is created with each drug dosage given or each drug dosageto be given, and the daily record is updated with each new record.

A normalized lab table is also created from lab data and stored withinthe laboratory database 57. The table is also comprised of achronological sequence of data records, with each data record havingdata fields identifying a patient ID, a time of the test, the lab name,and the lab result. A new record is created for every test result, andthe lab table is updated after the creation of each new record.

C. ADE Rules

As shown in FIG. 6, prior to the use of the ADE monitoring system, ADErules 64, 65 are created and stored within the ADE rule database 60.Each ADE rule contain a plurality of data fields therein which containinformation that is used by the ADE monitoring system to determine if anADE has occurred. The values which are contained in each data field areeither defined by or approved by a healthcare provider utilizing the ADErules. These ADE rules can include some created by a service whichprovides ADE monitoring 64 and some created by the medical facility 65.

As shown in FIG. 7, an ADE rule is a data record that includes aplurality of fields. In one embodiment, an ADE rule includes data fieldsfor search status 71, search type 72, target drug 73, target lab 74,drug lab/search name 75, severity 76, lab code 77, pattern 78, type 79,baseline 80, absolute 81, interval 82, danger multiplier 83, momentummultiplier 84, allergy 85, hospital unit 86, doctor(s) 87, diagnosis 88,gender 89, age range 90, concurrent drugs 91, concurrent labs 92, alerttemplate 93, description 94, and contact 95. A precursory explanation ofthe contents of each field are defined below, the functions of thesefields will be expanded further in the specification when needed todescribe the functionality of the subject invention.

Search Status 71 determines if a rule is to be used when performing ADEmonitoring. If enabled the rule is used by the subject ADE monitoringsystem.

Search Type 72, Drug/Lab Search Name, and Description 94 are all fieldsused to classify an ADE Rule. Search Type 72 is used to signify if anADE rule is a research rule or an alert rule. Alerts are specificallywritten to produce an alert procedure when satisfied. Research rules arespecifically made for research purposes only and do not need to triggeran alert procedure if satisfied. Drug/Lab Search Name 75 is a uniqueidentifier which represents a particular rule.

Target Drug 73 and Target Lab 74 are the drug and lab combination whichis the focus of an ADE rule. Target Drug 73 names the drug which is thebasis for the rule. Target Lab 74 names the lab test which is the basisfor the rule.

Severity 76 indicates the severity of the ADE.

Lab code 77 is a unique identifier for the Target Lab 74.

Pattern 78 specifies whether the rule is looking for a high or low labtest, and what is the normal drug response to the lab test (i.e. whetherto raise or lower the drug dosage.).

Type 79 and Baseline 80 are data fields used to determine if a lab valueis abnormal. Type 79 specifies whether the Baseline value 80 defines ahigh border or a low border of a normal lab result. Baseline 80represents a value that exceeds or fails to reach either a maximum orminimum normal value, respectively, for the Target Lab 74.

Absolute 81, Interval 82, Danger Multiplier 83, and Momentum Multiplier84 are all used to determine an appropriate waiting period wherein acorrective action is to be taken. Absolute 81 represents a lab testvalue that is considered dangerous. If the test value in a Drug/Lab datarecord is equal to or exceeds the Absolute 64 value then the ADEmonitoring system treats the situation as a medical emergency. Interval82 in the ADE rule contains the time interval (in hours) within whichthe ADE monitoring system expects an action to occur. The DangerMultiplier 83 contains a variable that automatically adjusts how quicklythe ADE monitoring system expects a response to an abnormal lab test,based upon how close the lab test is to an Absolute 81 value. MomentumMultiplier 84 includes a factor that takes the previous lab value intoconsideration and automatically adjusts the Interval accordingly.

Allergy 85 indicates an allergic reaction to a particular drug. Thisparameter is simply enabled or disabled. Once enabled and if thebaseline value is reached or exceeded, the only action capable ofremoving an alert would be the discontinuance of the Target Drug 73.This parameter does not depend on a history of allergy by the patientbut is a link with a particular lab test and result that can indicatethat the patient is allergic to the drug.

Hospital Unit 86, Doctor 87, Diagnosis 88, Gender 89 and Age Range 90,if defined, are additional requirements that must be satisfied if analert procedure is to be triggered. These parameters are referred to asdetail filters and they represent specific conditions which, if present,will override the continued processing of an abnormal lab condition.

Concurrent Drug 91 and Concurrent Lab 92 are associated conditions whichmust be present for an alert procedure to be triggered and are referredto as association filters. Concurrent Drug 91 names medications thatmust have been administered to a patient within a prescribed period ofthe abnormal lab for an alert condition to exist. Similarly, ConcurrentLab 67 lists additional tests and test values that must be presentwithin a prescribed period of the abnormal lab before an alert procedureis triggered.

Alert Template 93 and Contact 95 are used in sending an alert to ahealthcare provider. The Alert Template 93 contains the name of atemplate which defines how to handle an alert for the specific ADE ruleand Contact 95 lists who should be contacted if an alert is sent.

D. ADE Monitoring

As shown in FIG. 6, in one embodiment, ADE monitoring is performed byreceiving data from a healthcare provider's laboratory and pharmacyinformation systems and integrating and correlating the data. This datais then submitted to an ADE search engine 61 which searches an ADE ruledatabase 60 to see if the data satisfies any predefined ADE rule. If adefinition is satisfied, an alert procedure is activated to notify themedical facility of a potential ADE.

ADE monitoring can be done in real time by having the medical facilitytransmit applicable data as soon as it is received, and by having ADEmonitoring activated automatically upon reception of new laboratory andpharmacy data. Real time ADE monitoring allows nearly instantaneousdetection of ADE. The ADE monitoring system can also be activatedperiodically by allowing transmitted pharmacy and lab data to accumulatein pharmacy 56 and laboratory 57 databases and searching for matches atpredefined times, or upon activation by a user.

As shown in FIGS. 8 a and 9, in one embodiment, once ADE monitoring isactivated, the subject ADE monitoring system will first check to see ifan abnormal lab is received (box 100). This check is done by filteringdata located within the pharmacy 56 and lab 57 databases with theplurality of ADE rules stored within the ADE rules database to see if anADE rule is satisfied by the pharmacy and lab data.

The filtering process includes using the lab name stored within theTarget Drug 73 data field of an ADE rule to filter the drugs listed inthe daily record to determine if it was administered or is scheduled tobe administered to a patient during a predefined period. If a matchexists, the records within the lab table is then filtered using the datalocated within the Target Lab 74, Baseline 80, and Type 79 data fieldslocated in the same ADE rule to determine if an abnormal lab result hasbeen received.

As shown in FIG. 9, if a lab name located within the Target Lab 74 datafield matches a lab name in the lab table, then the value for the lab iscompared with the value within the Baseline 80 database for the same ADErule. If the lab value is equal to or exceeds (if Type 79 is high) or ifit does not exceed (if Type 79 is low) the value in the Baseline 80 datafield, then the lab value is an abnormal lab. After an abnormal labresult is detected and absent any additional criteria in the detailfilters or association filters, an ADE rule has been satisfied and analert procedure is triggered.

As shown in FIG. 11, the data fields Hospital Unit 86, Doctor 87,Diagnosis 88, Gender 89 and Age Range 90, comprise a detail filter that,if defined, are additional requirements that must also be satisfied ifan alert procedure is to be triggered. If a drug/lab match exists thenthe patient record is checked to see if the defined detail filters aresatisfied (Box 102). If any defined detail filters are not satisfied,then the drug/lab match is disregarded.

If a drug/lab match is found and the detail filters are satisfied, thesearch engine then checks the Concurrent Drug 91 and Concurrent Lab 92data fields to see if these association filters are defined (Box 103).As shown in FIG. 10, if any of the association filters are defined, thesearch engine filters through the daily record or the lab table,depending on which parameter is defined, to see if the associated drugwas administered or if the associate lab result occurred within apredefined period of time prior to the abnormal lab result. If theassociation filter is satisfied, then the ADE monitoring system canbegin an alert procedure. If they are not, then the drug/lab match isdisregarded.

E. Alert Procedures

As shown in FIGS. 8 a and 8 b, in one embodiment, an alert procedureincludes calculating an action date (box 104) which defines a waitingperiod wherein the system allows the problem to be resolved by themedical staff and allows time for additional tests to ensure that apotential ADE does exist (the abnormal lab value being erroneous). Theaction date is adjusted (boxes 105 and 106) to take into account aplurality of factors such as the current abnormal lab value, theprevious lab value, the amount of time between a previous lab and thecurrent abnormal lab, and the value of a current abnormal lab relativeto a potentially dangerous value for the lab.

During this waiting period prior to the action date, the system monitorsincoming pharmacy and laboratory data in order to determine if a propercorrective action is taken. The proper corrective action can bediscontinuing a medication or receiving a more recent test result or itcan be a response such as raising or lowering a dosage (the appropriatechange is listed in the Pattern 78 data field of the matched ADE rule).If the action date is reached without a proper corrective action beingtaken or if an inappropriate action has been taken (such as raising thedrug level when it should be lowered), an alert indicating the existenceof a potential ADE is generated and sent to the healthcare provider. Ifa proper action has been taken then the drug/lab match is disregarded.

A proper corrective action can be a discontinuation of the medication(box 107). As shown in FIG. 12 b, a discontinuation of a medication isdetected by the ADE monitoring system by monitoring the period of timestarting from the last administration of the medication to bediscontinued. A time interval (C) is defined which represents a periodsufficient to determine a discontinuance of a particular drug. If thetime interval between the last time a drug was administered and the endof the live pharmacy data is greater than (C), and if the drug was notadministered between that time, then the drug is effectivelydiscontinued and the drug/lab match is disregarded. If the interval (C)is not satisfied and there is no more data in the pharmacy database, thesystem will continue to monitor incoming lab results until the interval(C) is satisfied.

Another proper corrective action may also be receiving a more currentresult for the same Target Lab 74 (box 108). As shown in FIG. 12 a, oncean abnormal result (A) is received, subsequent tests are monitored tosee if a more recent lab result for the same test (B) is present withinthe lab table. If a more recent test is present, the lab/drug match isdisregarded.

In some instances, the proper corrective action can also be anadjustment to the dosage given a patient (Box 109). As shown in FIG. 12c, after an abnormal lab result occurs (A) the system monitorssubsequent pharmacy data to determine if an actual dosage given orplanned dose (B) includes a dosage which is lowered or raised as isrequired by the Pattern 78 data field in the matching ADE rule. If anactual dosage or a planned dosage is properly adjusted, the drug/labmatch is disregarded.

Absolute 81, Interval 82, Danger Multiplier 83, and Momentum Multiplier84 are all data fields within a matching ADE rule that are used todetermine an appropriate waiting period wherein a corrective action isto be taken. The Interval 82 data field in a matching ADE rule containsthe time interval (in hours) within which the ADE monitoring systemexpects an action to occur, and this time period is adjusted accordinglyto take into account a plurality of factors such as the current abnormallab value, the previous lab value, the amount of time between a previouslab and the current abnormal lab, and the value of a current abnormallab relative to a potentially dangerous value for the lab. The datewherein the interval expires and an alert is generated is called theaction date. The action date is calculated by the formula:

Action Date=I−(DM+(AM*MF))*((I*((HV−LV0/HV−AHV))))

Wherein

-   -   I—value in data field Interval 70 (FIG. 7)    -   DM—represents Danger Multiplier 71    -   AM—actual momentum    -   MF—represents a Momentum Multiplier 72    -   HV—represents the Baseline 63 value    -   AHV—represents the Absolute 64 value    -   LV—represents the recorded lab value

The Danger Multiplier 71 contains a variable that automatically adjustshow quickly the ADE monitoring system expects a response to an abnormallab test, based upon how close the lab test is to an Absolute 64 value.The variable is the slope of a linear function that governs how theinterval time is adjusted relative to the proximity of a lab test resultto the Absolute 71 value. FIG. 13 shows the formula to calculate anaction date adjusted for a danger factor. The variables in the formulacan be defined as:

LD2—date of abnormal lab value

IC—value in data field Interval 70 (FIG. 7)

DM—represents Danger Multiplier 71

LabHI—represents the Baseline 63 value

LV—abnormal lab value

LabAbsHi—represents the Absolute 64 value

Momentum 72 is determined by the value given to the Momentum Multiplier(MF) by the user and the found Actual Momentum (AM). The MomentumMultiplier (MF) is set by the user much like the Danger Multiplier (DM).It acts on the Actual Momentum (AM). Actual Momentum (AM) is calculatedby taking the difference in value between the current lab test and thelast previous one (LV2−LV1) and dividing by the time difference betweenthe dates of each (LD2−LD1). The value of the ratio is then correctedfor the absolute value of the lab tests by dividing by the most recentlab value (LV1).

FIG. 14 shows the formula to calculate the actual momentum and an actiondate adjusted by the momentum multiplier. The variables in the formulascan be defined as:

LD2—date of abnormal lab value

LV2—abnormal lab value (also referred to as Lab Value)

LV1—most recent lab value for same test

LD1—most recent date for same test

IC—value in data field Interval 70 (FIG. 7)

AM—represents the actual momentum

MF—represents a Momentum Multiplier 72

DM—represents Danger Multiplier 71

LabHI—represents the Baseline 63 value

LV—abnormal lab value

LabAbsHi—represents the Absolute 64 value

Once an action date is reached without an appropriate action beingundertaken, the system makes contact with the healthcare provider inorder to alert them of a potential ADE. The matching ADE rule includesthe name of an appropriate template in Alert Template 73, and adestination for the message in the Contact parameter 74. Preferably, theADE monitoring system delivers the alert through an electronic messagingsystem such as an E-mail. It is also contemplated that such alerts canalso be transmitted in a known manner through a paging system or a voicemail system to an attending physician. This electronic message may bereceived at a central point in a healthcare facility, and additionallyit may be received at a nursing station located in the medical wardwherein the patient is hospitalized.

As shown in FIG. 16, one embodiment of an alert includes a graphicalrepresentation of the medication dosage relative to lab test results160, a name of the rule satisfied, patient information 162, and drug/labinformation 163. In this embodiment, the alert is a page which islocated within a web site, but similar information may be transmitted toan email address, a central station within a health care organization,or a pharmacy.

F. Patient Reports

The ADE monitoring system stores data received from the medical facilityas well as the alerts which are generated in a database which isaccessible to users for patient care, quality assurance, or medicalresearch. Information within the database can be filtered and compiledby a user to provide specific information relating to a particularpatient or to a number of patients within a medical facility. Theinformation can be filtered and compiled via criteria determined throughan interactive query or through predefined report parameters. (need moreinfo on report generation capability)

In one embodiment, an individual patient report is generated utilizingan interactive query. The ADE monitoring system gives the user an optionto filter and graph a particular patient's information by defining anADE rule name, a target lab test, a target drug, an abnormal range, alab result high or low parameter, a danger level, recent start(instructing the database to consider only recent data), new date look(a feature which enables the computer to estimate what date an actionwould occur), and new date time (a feature which enables the computer toestimate what time an action would occur). As shown in FIG. 15 a, anindividual patient report can generate a graphical interpretation of thepatients data, or as shown in FIG. 15 b the information can be arrangedin a tabular format

In another embodiment, ADE monitoring system includes a reportgeneration application which can generate predefined reports such as asystem report which compiles predefined data for an entire system, anADE facility report which shows information for a specific facility, adrug management report which breaks out data according to drugs used,ADE reports which performs statistical analysis of ADE's, and an ADEdoctor report which shows information for a specific doctor. Thesereports are predefined and can be generated by simply selecting thefunction from a menu. As shown in FIG. 15 b, these reports can include aspecific ADE rule name, a total number of occurrences, a total number ofalerts, and a percentage of alerts respective of a total number ofoccurrences. Alerts such as those shown in FIG. 16 can also be accessedand reviewed individually.

G. User Operation

A user will typically access the ADE monitoring system 10 online bylogging onto a web site on a secured intranet. Every authorized userwill typically be assigned a unique log on ID and password to enableaccess. Each user is also typically assigned a security role whichlimits their ability to access certain information in the ADE monitoringsystem.

As shown in FIG. 18, once logged on, the user is greeted by a primaryinterface screen 100 which contains selections for navigating to theprimary functions of the ADE monitoring system 10. The primary screenincludes menu options which enable a user to run a search 101, consultADE results 102, and 103 and to create and modify ADE rules 104.

FIG. 19 a and 19 b shows a rule maintenance screen 110 to the ADEmonitoring system. The screen is used to create new ADE rules, modifyexisting ADE rules, check the contents of an ADE rule, and to copy thecontents of an ADE rule. The screen includes a plurality of data entryfields which enable a user to enter or change values for data fields ofan ADE rule.

FIG. 20 shows a search screen 120 which is used to run an ADE search. Auser may instantaneously activate the ADE monitoring process byselecting the Run button 121. A status window 122 defines the exact dateand time the ADE monitoring was run. After the ADE monitoring process iscompleted, the exit button 123 is enabled, and the user can then go backto the primary interface screen 100 by selecting it.

Once back in the primary interface screen 100, the user can view ADEmonitoring results by selecting the Alert View 102 and Alert Analysis103 options. The ADE monitoring results can then be displayed based on aparticular individual or a group of individuals by using the patientreports procedures outlined above.

While the present invention has been described with reference to severalembodiments thereof, those skilled in the art will recognize variouschanges that may be made without departing from the spirit and scope ofthe claimed invention. Accordingly, this invention is not limited towhat is shown in the drawings and described in the specification butonly as indicated in the appended claims, nor is the claimed inventionlimited in applicability to one type of computer or computer network.Any numbering or ordering of elements in the following claims is merelyfor convenience and is not intended to suggest that the ordering of theelements of the claims has any particular significance other than thatotherwise expressed by the language of the claim.

1. A method of anticipating adverse drug episodes comprising: defining aplurality of ADE rules having data fields for a lab test name, a valuefor the lab test, and a drug; and filtering a patient's lab data andpharmacy data using the plurality of definitions.
 2. The method of claim1, and further comprising the additional step of creating a normalizeddrug table from a patient's pharmacy data, the pharmacy table havingdata fields for each drug administered, a dosage, and a timeadministered.
 3. The method of claim 2, and further comprising theadditional step of creating a normalized lab table from a patient's labdata, the lab table having data fields for a patient id, time of test,name of test, and a test result.
 4. The method of claim 3, wherein thestep of filtering includes the steps of extracting a lab name, a resultof the lab from the lab table and a drug from the drug table andmatching it to a lab name, lab result and drug within an ADE rule. 5.The method of claim 1, and further comprising the additional step ofimporting laboratory data and pharmacy data from a healthcare facility.6. The method of claim 5, and further comprising the additional step ofverifying imported lab data or pharmacy data is formatted in accordancewith a predefined format.
 7. The method of claim 1, and furthercomprising the additional steps of computing a cumulative dosage for adrug within a 24 hour period from a date of administration.
 8. Themethod of claim 1, wherein the ADE rules also includes a data fieldcontaining a waiting period for a proper corrective action.
 9. Themethod of claim 8, and further comprising the additional steps offiltering subsequent lab data or pharmacy data to determine if a propercorrective action has occurred.
 10. The method of claim 9, and furthercomprising the additional step of alerting a health care provider when awaiting period for a proper corrective action has expired without aproper corrective action occurring.
 11. The method of claim 8, andfurther comprising the additional step of adjusting a waiting periodbased on a test lab value.
 12. The method of claim 8 and furthercomprising the additional step of adjusting a waiting period based onprevious lab test values.
 13. The method of claim 1, wherein thelab/data definition includes data fields for associated drugs.
 14. Themethod of claim 13, further comprising the additional step of filteringa patient's previous pharmacy data for an associated drug.
 15. Themethod of claim 1, wherein the lab/data definition includes data fieldsfor an associated test lab and result.
 16. The method of claim 15,further comprising the additional step of filtering a patient's lab datafor an associated test lab and result.
 17. A system for anticipatingadverse drug events comprising: a central processor having a searchengine therein; and an ADE rule database in communication with theserver.
 18. The system of claim 17, wherein the central processor is incommunication with a computer network.
 19. The system of claim 18,wherein the computer network. is an intranet.
 20. The system of claim17, and further comprising a laboratory and a pharmacy database.
 21. Thesystem of claim 17, wherein the central processor includes a web serverhosting a web site therein and in communication with an intranet. 22.The system of claim 17, wherein the central processor is incommunication with a pharmacy information system and a laboratoryinformation system.
 23. The system of claim 17, wherein the centralprocessor is in communication with a nursing station at a medicalfacility.
 24. The system of claim 17, wherein the central processor isin communication with a paging system.
 25. The system of claim 17,wherein the central processor includes a web server, an applicationserver, a database server, and a directory server.
 26. The system ofclaim 17 wherein the central processor includes an application forreformatting and integrating pharmacy data and lab data.
 27. A method ofanticipating adverse drug episodes comprising: defining a plurality ofADE rules having data fields for a lab test name, a value for the labtest, and a drug; storing the ADE rules within an ADE rules database;importing a patient's lab data and pharmacy data; storing a patient'slab result, the lab test name, and a name of a drug administered to thepatient within a database; matching a patient's lab result, test name,and administered drug with a lab value, lab name and drug within an ADErule.
 28. The method of claim 27, and further comprising the additionalsteps of extracting a lab test name, a lab test result from a patient'slab data and extracting a drug name from a patient's pharmacy data. 29.The method of claim 27, wherein the step of storing includes the stepsof storing a patient's lab result and the lab test name within a labdatabase and storing a name of a drug administered within a pharmacydatabase.
 30. The method of claim 27, and further comprising theadditional steps alerting a health care provider when a match occurs.31. The method of claim 27, and further comprising the additional stepof storing a patient's hospital unit, doctor, diagnosis, gender, and agewithin a database.
 32. The method of claim 31, wherein the ADE ruleincludes a data field for storing a hospital unit, doctor, diagnosis,gender, and age.
 33. The method of claim 32, and further comprising theadditional steps of matching a patient's hospital unit, doctor,diagnosis, gender, and age with a respective value in an ADE rule.